A satellite-based disturbance index algorithm for monitoring mitigation strategies effects on desertification change in an arid environment

This research focuses on monitoring the desertification change as a result of mitigation and adaptation strategies in arid environmental condition. Exploring environmental hazards, specifically desertification development, is important for understanding loss of productivity in dry lands. Developing a new satellite-based algorithm for monitoring desertification in an arid environment delivers information useful in protecting the environment and mitigating natural hazards. A multi-temporal remote sensing data of MODerate resolution Imaging Spectroradiometer (MODIS) were used for estimating the Soil-Adjusted Vegetation Index (SAVI) and Land Surface Temperature (LST), based on monthly data during the years 2002, 2005, 2008 and 2011. The MODIS-based disturbance index (MBDI) was improved by estimating the long-term variation in the ratio of annual maximum composite LST and SAVI on a pixel-by-pixel basis. A significant correlation (r = -0.88; P < 0.001) was found between the mean-maximum SAVI and mean-maximum LST in the dry season. The response of the MBDI to land degradation was assessed by comparing the obtained soil salinity data to the algorithm outcomes. The results showed that the proposed new satellite-based algorithm has a high potential to detect the spatial extent of prime land degradation in an arid environment. Also, this algorithm was able to recognize the difference between the natural variability and instantaneous/non-instantaneous desertification symptoms in an arid environment. The mitigation strategies in the case study decreased the desertification development and combat the land degradation in the last decade